{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "mAWHDEbr6Q2i"
      },
      "source": [
        "[![Open in colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/open-mmlab/mmdeploy/tree/main/demo/tutorials_1.ipynb)\n",
        "# 前言\n",
        "OpenMMLab 的算法如何部署？是很多社区用户的困惑。而模型部署工具箱 [MMDeploy](https://zhuanlan.zhihu.com/p/450342651) 的开源，强势打通了从算法模型到应用程序这 \"最后一公里\"！\n",
        "今天我们将开启模型部署入门系列教程，在模型部署开源库 MMDeploy 的辅助下，介绍以下内容：\n",
        "\n",
        "\n",
        "*   中间表示 ONNX 的定义标准\n",
        "*   PyTorch 模型转换到 ONNX 模型的方法\n",
        "*   推理引擎 ONNX Runtime、TensorRT 的使用方法\n",
        "*   部署流水线 PyTorch - ONNX - ONNX Runtime/TensorRT 的示例及常见部署问题的解决方法\n",
        "*   MMDeploy C/C++ 推理 SDK\n",
        "希望通过本系列教程，带领大家学会如何把自己的 PyTorch 模型部署到 ONNX Runtime/TensorRT 上，并学会如何把 OpenMMLab 开源体系中各个计算机视觉任务的模型用 [MMDeploy](https://zhuanlan.zhihu.com/p/450342651) 部署到各个推理引擎上。\n",
        "\n",
        "**我们默认大家熟悉 Python 语言，并对 PyTorch 框架有基本的认识，除此之外不需要了解任何模型部署的知识。**\n",
        "\n",
        "在第一篇文章中，我们将部署一个简单的超分辨率模型，认识中间表示、推理引擎等模型部署中的概念。 \n"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "nJxQ-uXB1ULa"
      },
      "source": [
        "# 初识模型部署\n",
        "在软件工程中，部署指把开发完毕的软件投入使用的过程，包括环境配置、软件安装等步骤。类似地，对于深度学习模型来说，模型部署指让训练好的模型在特定环境中运行的过程。相比于软件部署，模型部署会面临更多的难题：\n",
        "\n",
        "1）运行模型所需的环境难以配置。深度学习模型通常是由一些框架编写，比如 PyTorch、TensorFlow。由于框架规模、依赖环境的限制，这些框架不适合在手机、开发板等生产环境中安装。\n",
        "\n",
        "2）深度学习模型的结构通常比较庞大，需要大量的算力才能满足实时运行的需求。模型的运行效率需要优化。\n",
        "\n",
        "因为这些难题的存在，模型部署不能靠简单的环境配置与安装完成。经过工业界和学术界数年的探索，模型部署有了一条流行的流水线：\n",
        "\n",
        "![pipeline](https://user-images.githubusercontent.com/4560679/156556619-3da7a572-876b-4909-b26f-04e81190c546.png)\n",
        "\n",
        "为了让模型最终能够部署到某一环境上，开发者们可以使用任意一种**深度学习框架**来定义网络结构，并通过训练确定网络中的参数。之后，模型的结构和参数会被转换成一种只描述网络结构的**中间表示**，一些针对网络结构的优化会在中间表示上进行。最后，用面向硬件的高性能编程框架(如 CUDA，OpenCL）编写，能高效执行深度学习网络中算子的推理引擎会把中间表示转换成特定的文件格式，并在对应硬件平台上高效运行模型。\n",
        "\n",
        "这一条流水线解决了模型部署中的两大问题：使用对接深度学习框架和**推理引擎**的中间表示，开发者不必担心如何在新环境中运行各个复杂的框架；通过中间表示的网络结构优化和推理引擎对运算的底层优化，模型的运算效率大幅提升。\n",
        "\n",
        "现在，让我们从一个模型部署的“Hello World”项目入手，见识一下模型部署各方面的知识吧！\n",
        "\n",
        "# 部署第一个模型\n",
        "## 创建 PyTorch 模型\n",
        "让我们用 PyTorch 实现一个超分辨率模型，并把模型部署到 ONNX Runtime 这个推理引擎上。\n",
        "\n",
        "首先，我们需要创建一个有 PyTorch 库的 Python 编程环境。"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "dAAZ7qdJ16Jo",
        "outputId": "0461102c-f669-4f16-d97a-d8a98150666b"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "nvcc: NVIDIA (R) Cuda compiler driver\n",
            "Copyright (c) 2005-2020 NVIDIA Corporation\n",
            "Built on Mon_Oct_12_20:09:46_PDT_2020\n",
            "Cuda compilation tools, release 11.1, V11.1.105\n",
            "Build cuda_11.1.TC455_06.29190527_0\n",
            "gcc (Ubuntu 7.5.0-3ubuntu1~18.04) 7.5.0\n",
            "Copyright (C) 2017 Free Software Foundation, Inc.\n",
            "This is free software; see the source for copying conditions.  There is NO\n",
            "warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.\n",
            "\n"
          ]
        }
      ],
      "source": [
        "# 检查nvcc版本\n",
        "!nvcc -V\n",
        "# 检查gcc版本\n",
        "!gcc --version"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "Y5knBfH63KFb",
        "outputId": "a1a51caa-4222-4e0c-cda3-3adb52401e0a"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Looking in links: https://download.pytorch.org/whl/lts/1.8/torch_lts.html\n",
            "Collecting torch==1.8.2+cu111\n",
            "  Downloading https://download.pytorch.org/whl/lts/1.8/cu111/torch-1.8.2%2Bcu111-cp37-cp37m-linux_x86_64.whl (1982.2 MB)\n",
            "\u001b[K     |█████████████▌                  | 834.1 MB 1.6 MB/s eta 0:11:43tcmalloc: large alloc 1147494400 bytes == 0x5613cfd9a000 @  0x7f1182a1e615 0x5613964f13bc 0x5613965d218a 0x5613964f41cd 0x5613965e6b3d 0x561396568458 0x56139656302f 0x5613964f5aba 0x5613965682c0 0x56139656302f 0x5613964f5aba 0x561396564cd4 0x5613965e7986 0x561396564350 0x5613965e7986 0x561396564350 0x5613965e7986 0x561396564350 0x5613964f5f19 0x561396539a79 0x5613964f4b32 0x5613965681dd 0x56139656302f 0x5613964f5aba 0x561396564cd4 0x56139656302f 0x5613964f5aba 0x561396563eae 0x5613964f59da 0x561396564108 0x56139656302f\n",
            "\u001b[K     |█████████████████               | 1055.7 MB 1.4 MB/s eta 0:11:10tcmalloc: large alloc 1434370048 bytes == 0x5614143f0000 @  0x7f1182a1e615 0x5613964f13bc 0x5613965d218a 0x5613964f41cd 0x5613965e6b3d 0x561396568458 0x56139656302f 0x5613964f5aba 0x5613965682c0 0x56139656302f 0x5613964f5aba 0x561396564cd4 0x5613965e7986 0x561396564350 0x5613965e7986 0x561396564350 0x5613965e7986 0x561396564350 0x5613964f5f19 0x561396539a79 0x5613964f4b32 0x5613965681dd 0x56139656302f 0x5613964f5aba 0x561396564cd4 0x56139656302f 0x5613964f5aba 0x561396563eae 0x5613964f59da 0x561396564108 0x56139656302f\n",
            "\u001b[K     |█████████████████████▋          | 1336.2 MB 1.3 MB/s eta 0:08:10tcmalloc: large alloc 1792966656 bytes == 0x561399222000 @  0x7f1182a1e615 0x5613964f13bc 0x5613965d218a 0x5613964f41cd 0x5613965e6b3d 0x561396568458 0x56139656302f 0x5613964f5aba 0x5613965682c0 0x56139656302f 0x5613964f5aba 0x561396564cd4 0x5613965e7986 0x561396564350 0x5613965e7986 0x561396564350 0x5613965e7986 0x561396564350 0x5613964f5f19 0x561396539a79 0x5613964f4b32 0x5613965681dd 0x56139656302f 0x5613964f5aba 0x561396564cd4 0x56139656302f 0x5613964f5aba 0x561396563eae 0x5613964f59da 0x561396564108 0x56139656302f\n",
            "\u001b[K     |███████████████████████████▎    | 1691.1 MB 1.3 MB/s eta 0:03:43tcmalloc: large alloc 2241208320 bytes == 0x56140400a000 @  0x7f1182a1e615 0x5613964f13bc 0x5613965d218a 0x5613964f41cd 0x5613965e6b3d 0x561396568458 0x56139656302f 0x5613964f5aba 0x5613965682c0 0x56139656302f 0x5613964f5aba 0x561396564cd4 0x5613965e7986 0x561396564350 0x5613965e7986 0x561396564350 0x5613965e7986 0x561396564350 0x5613964f5f19 0x561396539a79 0x5613964f4b32 0x5613965681dd 0x56139656302f 0x5613964f5aba 0x561396564cd4 0x56139656302f 0x5613964f5aba 0x561396563eae 0x5613964f59da 0x561396564108 0x56139656302f\n",
            "\u001b[K     |████████████████████████████████| 1982.2 MB 1.2 MB/s eta 0:00:01tcmalloc: large alloc 1982201856 bytes == 0x56148996c000 @  0x7f1182a1d1e7 0x5613965275d7 0x5613964f13bc 0x5613965d218a 0x5613964f41cd 0x5613965e6b3d 0x561396568458 0x56139656302f 0x5613964f5aba 0x561396564108 0x56139656302f 0x5613964f5aba 0x561396564108 0x56139656302f 0x5613964f5aba 0x561396564108 0x56139656302f 0x5613964f5aba 0x561396564108 0x56139656302f 0x5613964f5aba 0x561396564108 0x5613964f59da 0x561396564108 0x56139656302f 0x5613964f5aba 0x561396564cd4 0x56139656302f 0x5613964f5aba 0x561396564cd4 0x56139656302f\n",
            "tcmalloc: large alloc 2477752320 bytes == 0x561574036000 @  0x7f1182a1e615 0x5613964f13bc 0x5613965d218a 0x5613964f41cd 0x5613965e6b3d 0x561396568458 0x56139656302f 0x5613964f5aba 0x561396564108 0x56139656302f 0x5613964f5aba 0x561396564108 0x56139656302f 0x5613964f5aba 0x561396564108 0x56139656302f 0x5613964f5aba 0x561396564108 0x56139656302f 0x5613964f5aba 0x561396564108 0x5613964f59da 0x561396564108 0x56139656302f 0x5613964f5aba 0x561396564cd4 0x56139656302f 0x5613964f5aba 0x561396564cd4 0x56139656302f 0x5613964f6151\n",
            "\u001b[K     |████████████████████████████████| 1982.2 MB 6.6 kB/s \n",
            "\u001b[?25hCollecting torchvision==0.9.2+cu111\n",
            "  Downloading https://download.pytorch.org/whl/lts/1.8/cu111/torchvision-0.9.2%2Bcu111-cp37-cp37m-linux_x86_64.whl (17.5 MB)\n",
            "\u001b[K     |████████████████████████████████| 17.5 MB 1.6 MB/s \n",
            "\u001b[?25hCollecting torchaudio==0.8.2\n",
            "  Downloading https://download.pytorch.org/whl/lts/1.8/torchaudio-0.8.2-cp37-cp37m-linux_x86_64.whl (1.9 MB)\n",
            "\u001b[K     |████████████████████████████████| 1.9 MB 6.0 MB/s \n",
            "\u001b[?25hRequirement already satisfied: numpy in /usr/local/lib/python3.7/dist-packages (from torch==1.8.2+cu111) (1.21.5)\n",
            "Requirement already satisfied: typing-extensions in /usr/local/lib/python3.7/dist-packages (from torch==1.8.2+cu111) (3.10.0.2)\n",
            "Requirement already satisfied: pillow>=4.1.1 in /usr/local/lib/python3.7/dist-packages (from torchvision==0.9.2+cu111) (7.1.2)\n",
            "Installing collected packages: torch, torchvision, torchaudio\n",
            "  Attempting uninstall: torch\n",
            "    Found existing installation: torch 1.10.0+cu111\n",
            "    Uninstalling torch-1.10.0+cu111:\n",
            "      Successfully uninstalled torch-1.10.0+cu111\n",
            "  Attempting uninstall: torchvision\n",
            "    Found existing installation: torchvision 0.11.1+cu111\n",
            "    Uninstalling torchvision-0.11.1+cu111:\n",
            "      Successfully uninstalled torchvision-0.11.1+cu111\n",
            "  Attempting uninstall: torchaudio\n",
            "    Found existing installation: torchaudio 0.10.0+cu111\n",
            "    Uninstalling torchaudio-0.10.0+cu111:\n",
            "      Successfully uninstalled torchaudio-0.10.0+cu111\n",
            "\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "torchtext 0.11.0 requires torch==1.10.0, but you have torch 1.8.2+cu111 which is incompatible.\u001b[0m\n",
            "Successfully installed torch-1.8.2+cu111 torchaudio-0.8.2 torchvision-0.9.2+cu111\n",
            "Collecting onnxruntime==1.8.1\n",
            "  Downloading onnxruntime-1.8.1-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (4.5 MB)\n",
            "\u001b[K     |████████████████████████████████| 4.5 MB 7.5 MB/s \n",
            "\u001b[?25hCollecting onnx\n",
            "  Downloading onnx-1.11.0-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (12.8 MB)\n",
            "\u001b[K     |████████████████████████████████| 12.8 MB 38.6 MB/s \n",
            "\u001b[?25hRequirement already satisfied: opencv-python in /usr/local/lib/python3.7/dist-packages (4.1.2.30)\n",
            "Requirement already satisfied: protobuf in /usr/local/lib/python3.7/dist-packages (from onnxruntime==1.8.1) (3.17.3)\n",
            "Requirement already satisfied: numpy>=1.16.6 in /usr/local/lib/python3.7/dist-packages (from onnxruntime==1.8.1) (1.21.5)\n",
            "Requirement already satisfied: flatbuffers in /usr/local/lib/python3.7/dist-packages (from onnxruntime==1.8.1) (2.0)\n",
            "Requirement already satisfied: typing-extensions>=3.6.2.1 in /usr/local/lib/python3.7/dist-packages (from onnx) (3.10.0.2)\n",
            "Requirement already satisfied: six>=1.9 in /usr/local/lib/python3.7/dist-packages (from protobuf->onnxruntime==1.8.1) (1.15.0)\n",
            "Installing collected packages: onnxruntime, onnx\n",
            "Successfully installed onnx-1.11.0 onnxruntime-1.8.1\n"
          ]
        }
      ],
      "source": [
        "# 安装 cuda 11.1 的 PyTorch \n",
        "# 如果你用的是其他版本的 cuda，请参考 PyTorch 的官方安装教程选择安装命令 \n",
        "!pip install torch==1.8.2+cu111 torchvision==0.9.2+cu111 -f https://download.pytorch.org/whl/lts/1.8/torch_lts.html\n",
        "# 安装 ONNX Runtime, ONNX, OpenCV \n",
        "!pip install onnxruntime==1.8.1 onnx opencv-python"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "Z-_3PEwW37Em"
      },
      "source": [
        "在一切都配置完毕后，用下面的代码来创建一个经典的超分辨率模型 SRCNN。"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 12,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 521
        },
        "id": "4Bk1bkp03-DA",
        "outputId": "d0a27fe1-1ac4-45b3-e37f-932a27d97d5d"
      },
      "outputs": [
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        },
        {
          "data": {
            "image/png": 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",
            "text/plain": [
              "<Figure size 432x288 with 1 Axes>"
            ]
          },
          "metadata": {
            "needs_background": "light"
          },
          "output_type": "display_data"
        }
      ],
      "source": [
        "import os\n",
        " \n",
        "import cv2 \n",
        "from matplotlib import pyplot as plt\n",
        "import numpy as np \n",
        "import requests \n",
        "import torch \n",
        "import torch.onnx \n",
        "from torch import nn \n",
        "\n",
        "class SuperResolutionNet(nn.Module):\n",
        "    def __init__(self, upscale_factor):\n",
        "        super().__init__()\n",
        "        self.upscale_factor = upscale_factor\n",
        "        self.img_upsampler = nn.Upsample(\n",
        "            scale_factor=self.upscale_factor,\n",
        "            mode='bicubic',\n",
        "            align_corners=False)\n",
        " \n",
        "        self.conv1 = nn.Conv2d(3,64,kernel_size=9,padding=4)\n",
        "        self.conv2 = nn.Conv2d(64,32,kernel_size=1,padding=0)\n",
        "        self.conv3 = nn.Conv2d(32,3,kernel_size=5,padding=2)\n",
        "\n",
        "        self.relu = nn.ReLU()\n",
        " \n",
        "    def forward(self, x):\n",
        "        x = self.img_upsampler(x)\n",
        "        out = self.relu(self.conv1(x))\n",
        "        out = self.relu(self.conv2(out))\n",
        "        out = self.conv3(out)\n",
        "        return out\n",
        " \n",
        "# Download checkpoint and test image \n",
        "urls = ['https://download.openmmlab.com/mmediting/restorers/srcnn/srcnn_x4k915_1x16_1000k_div2k_20200608-4186f232.pth', \n",
        "    'https://raw.githubusercontent.com/open-mmlab/mmediting/master/tests/data/face/000001.png']\n",
        "names = ['srcnn.pth', 'face.png']\n",
        "for url, name in zip(urls, names):\n",
        "    if not os.path.exists(name):\n",
        "        open(name, 'wb').write(requests.get(url).content)\n",
        " \n",
        "def init_torch_model():\n",
        "    torch_model = SuperResolutionNet(upscale_factor=3)\n",
        " \n",
        "    state_dict = torch.load('srcnn.pth')['state_dict']\n",
        " \n",
        "    # Adapt the checkpoint\n",
        "    for old_key in list(state_dict.keys()):\n",
        "        new_key = '.'.join(old_key.split('.')[1:])\n",
        "        state_dict[new_key] = state_dict.pop(old_key)\n",
        " \n",
        "    torch_model.load_state_dict(state_dict)\n",
        "    torch_model.eval()\n",
        "    return torch_model\n",
        " \n",
        "model = init_torch_model()\n",
        "input_img = cv2.imread('face.png')\n",
        "plt.imshow(cv2.cvtColor(input_img,cv2.COLOR_BGR2RGB))\n",
        "plt.show()\n",
        "input_img = input_img.astype(np.float32)\n",
        "# HWC to NCHW \n",
        "input_img = np.transpose(input_img, [2, 0, 1])\n",
        "input_img = np.expand_dims(input_img, 0)\n",
        " \n",
        "# Inference \n",
        "torch_output = model(torch.from_numpy(input_img)).detach().numpy()\n",
        " \n",
        "# NCHW to HWC \n",
        "torch_output = np.squeeze(torch_output, 0)\n",
        "torch_output = np.clip(torch_output, 0, 255)\n",
        "torch_output = np.transpose(torch_output, [1, 2, 0]).astype(np.uint8)\n",
        " \n",
        "# Show image \n",
        "cv2.imwrite(\"face_torch.png\", torch_output)\n",
        "\n",
        "plt.imshow(cv2.cvtColor(torch_output,cv2.COLOR_BGR2RGB))\n",
        "plt.show()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "lp02VxnL4JII"
      },
      "source": [
        "SRCNN 先把图像上采样到对应分辨率，再用 3 个卷积层处理图像。为了方便起见，我们跳过训练网络的步骤，直接下载模型权重（由于 MMEditing 中 SRCNN 的权重结构和我们定义的模型不太一样，我们修改了权重字典的 key 来适配我们定义的模型），同时下载好输入图片。为了让模型输出成正确的图片格式，我们把模型的输出转换成 HWC 格式，并保证每一通道的颜色值都在 0~255 之间。如果脚本正常运行的话，一幅超分辨率的人脸照片会保存在 “face_torch.png” 中。\n",
        "\n",
        "![face_torch](https://user-images.githubusercontent.com/4560679/156558692-e5b82284-22d1-434b-aace-b565ac223e73.png)\n",
        "\n",
        "在 PyTorch 模型测试正确后，我们来正式开始部署这个模型。我们下一步的任务是把 PyTorch 模型转换成用中间表示 ONNX 描述的模型。\n",
        "## 中间表示 - ONNX\n",
        "在介绍 ONNX 之前，我们先从本质上来认识一下神经网络的结构。神经网络实际上只是描述了数据计算的过程，其结构可以用计算图表示。比如 a+b 可以用下面的计算图来表示：\n",
        "\n",
        "![a+b](https://user-images.githubusercontent.com/4560679/156558717-96bbe544-4dc7-4460-8850-3cb1790e39ec.png)\n",
        "\n",
        "为了加速计算，一些框架会使用对神经网络“先编译，后执行”的静态图来描述网络。静态图的缺点是难以描述控制流（比如 if-else 分支语句和 for 循环语句），直接对其引入控制语句会导致产生不同的计算图。比如循环执行 n 次 a=a+b，对于不同的 n，会生成不同的计算图：\n",
        "\n",
        "![n=2](https://user-images.githubusercontent.com/4560679/156558606-6ff18e19-f3b1-463f-8f83-60bf6f7ef64b.png)\n",
        "\n",
        "ONNX （Open Neural Network Exchange）是 Facebook 和微软在2017年共同发布的，用于标准描述计算图的一种格式。目前，在数家机构的共同维护下，ONNX 已经对接了多种深度学习框架和多种推理引擎。因此，ONNX 被当成了深度学习框架到推理引擎的桥梁，就像编译器的中间语言一样。由于各框架兼容性不一，我们通常只用 ONNX 表示更容易部署的静态图。\n",
        "\n",
        "让我们用下面的代码来把 PyTorch 的模型转换成 ONNX 格式的模型："
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "6a8bZDui474h"
      },
      "outputs": [],
      "source": [
        "x = torch.randn(1, 3, 256, 256)\n",
        "\n",
        "with torch.no_grad():\n",
        "    torch.onnx.export(\n",
        "        model,\n",
        "        x,\n",
        "        \"srcnn.onnx\",\n",
        "        opset_version=11,\n",
        "        input_names=['input'],\n",
        "        output_names=['output'])"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "tEUmJIF053lI"
      },
      "source": [
        "其中，**torch.onnx.export** 是 PyTorch 自带的把模型转换成 ONNX 格式的函数。让我们先看一下前三个必选参数：前三个参数分别是要转换的模型、模型的任意一组输入、导出的 ONNX 文件的文件名。转换模型时，需要原模型和输出文件名是很容易理解的，但为什么需要为模型提供一组输入呢？这就涉及到 ONNX 转换的原理了。从 PyTorch 的模型到 ONNX 的模型，本质上是一种语言上的翻译。直觉上的想法是像编译器一样彻底解析原模型的代码，记录所有控制流。但前面也讲到，我们通常只用 ONNX 记录不考虑控制流的静态图。因此，PyTorch 提供了一种叫做追踪（trace）的模型转换方法：给定一组输入，再实际执行一遍模型，即把这组输入对应的计算图记录下来，保存为 ONNX 格式。export 函数用的就是追踪导出方法，需要给任意一组输入，让模型跑起来。我们的测试图片是三通道，256x256大小的，这里也构造一个同样形状的随机张量。\n",
        "\n",
        "剩下的参数中，opset_version 表示 ONNX 算子集的版本。深度学习的发展会不断诞生新算子，为了支持这些新增的算子，ONNX会经常发布新的算子集，目前已经更新15个版本。我们令 opset_version = 11，即使用第11个 ONNX 算子集，是因为 SRCNN 中的 bicubic （双三次插值）在 opset11 中才得到支持。剩下的两个参数 input_names, output_names 是输入、输出 tensor 的名称，我们稍后会用到这些名称。\n",
        "\n",
        "如果上述代码运行成功，目录下会新增一个\"srcnn.onnx\"的 ONNX 模型文件。我们可以用下面的脚本来验证一下模型文件是否正确。"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "QCcECxU959TW",
        "outputId": "2e46f06b-49ba-47af-d8b0-e2335d91684c"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Model correct\n"
          ]
        }
      ],
      "source": [
        "import onnx\n",
        " \n",
        "onnx_model = onnx.load(\"srcnn.onnx\")\n",
        "try:\n",
        "    onnx.checker.check_model(onnx_model)\n",
        "except Exception:\n",
        "    print(\"Model incorrect\")\n",
        "else:\n",
        "    print(\"Model correct\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "f9hh54Rj5_Vj"
      },
      "source": [
        "其中，**onnx.load** 函数用于读取一个 ONNX 模型。**onnx.checker.check_model** 用于检查模型格式是否正确，如果有错误的话该函数会直接报错。我们的模型是正确的，控制台中应该会打印出\"Model correct\"。\n",
        "\n",
        "接下来，让我们来看一看 ONNX 模型具体的结构是怎么样的。我们可以使用 **Netron** （开源的模型可视化工具）来可视化 ONNX 模型。把 srcnn.onnx 文件从本地的文件系统拖入网站，即可看到如下的可视化结果：\n",
        "\n",
        "![model](https://user-images.githubusercontent.com/4560679/156558675-df96e7f8-0c90-4b52-81db-f80e21e522a1.png)\n",
        "\n",
        "点击 input 或者 output，可以查看 ONNX 模型的基本信息，包括模型的版本信息，以及模型输入、输出的名称和数据类型。\n",
        "\n",
        "![model_property](https://user-images.githubusercontent.com/4560679/156558624-0d77bf2c-bd01-40e3-a89c-1b0f69329576.png)\n",
        "\n",
        "点击某一个算子节点，可以看到算子的具体信息。比如点击第一个 Conv 可以看到：\n",
        "\n",
        "![node_property](https://user-images.githubusercontent.com/4560679/156558668-867ea202-9ac2-4a04-b836-91ced4f2e5ea.png)\n",
        "\n",
        "每个算子记录了算子属性、图结构、权重三类信息。\n",
        "\n",
        "*   算子属性信息即图中 attributes 里的信息，对于卷积来说，算子属性包括了卷积核大小(kernel_shape)、卷积步长(strides)等内容。这些算子属性最终会用来生成一个具体的算子。\n",
        "*   图结构信息指算子节点在计算图中的名称、邻边的信息。对于图中的卷积来说，该算子节点叫做 Conv_2，输入数据叫做 11，输出数据叫做 12。根据每个算子节点的图结构信息，就能完整地复原出网络的计算图。\n",
        "*   权重信息指的是网络经过训练后，算子存储的权重信息。对于卷积来说，权重信息包括卷积核的权重值和卷积后的偏差值。点击图中 conv1.weight, conv1.bias 后面的加号即可看到权重信息的具体内容。\n",
        "现在，我们有了 SRCNN 的 ONNX 模型。让我们看看最后该如何把这个模型运行起来。"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "P80yIyaD-SVI"
      },
      "source": [
        "## 推理引擎 -ONNX Runtime\n",
        "**ONNX Runtime** 是由微软维护的一个跨平台机器学习推理加速器，也就是我们前面提到的”推理引擎“。ONNX Runtime 是直接对接 ONNX 的，即 ONNX Runtime 可以直接读取并运行 .onnx 文件, 而不需要再把 .onnx 格式的文件转换成其他格式的文件。也就是说，对于 PyTorch - ONNX - ONNX Runtime 这条部署流水线，只要在目标设备中得到 .onnx 文件，并在 ONNX Runtime 上运行模型，模型部署就算大功告成了。\n",
        "\n",
        "通过刚刚的操作，我们把 PyTorch 编写的模型转换成了 ONNX 模型，并通过可视化检查了模型的正确性。最后，让我们用 ONNX Runtime 运行一下模型，完成模型部署的最后一步。\n",
        "\n",
        "ONNX Runtime 提供了 Python 接口。接着刚才的脚本，我们可以添加如下代码运行模型："
      ]
    },
    {
      "cell_type": "code",
      "execution_count": null,
      "metadata": {
        "id": "EnXyju9--UNo"
      },
      "outputs": [],
      "source": [
        "import onnxruntime\n",
        "\n",
        "ort_session = onnxruntime.InferenceSession(\"srcnn.onnx\")\n",
        "ort_inputs = {'input': input_img}\n",
        "ort_output = ort_session.run(['output'], ort_inputs)[0]\n",
        "\n",
        "ort_output = np.squeeze(ort_output, 0)\n",
        "ort_output = np.clip(ort_output, 0, 255)\n",
        "ort_output = np.transpose(ort_output, [1, 2, 0]).astype(np.uint8)\n",
        "cv2.imwrite(\"face_ort.png\", ort_output)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "kE6nCBPC-cbK"
      },
      "source": [
        "这段代码中，除去后处理操作外，和 ONNX Runtime 相关的代码只有三行。让我们简单解析一下这三行代码。**onnxruntime.InferenceSession** 用于获取一个 ONNX Runtime 推理器，其参数是用于推理的 ONNX 模型文件。推理器的 run 方法用于模型推理，其第一个参数为输出张量名的列表，第二个参数为输入值的字典。其中输入值字典的 key 为张量名，value 为 numpy 类型的张量值。输入输出张量的名称需要和 **torch.onnx.export** 中设置的输入输出名对应。\n",
        "\n",
        "如果代码正常运行的话，另一幅超分辨率照片会保存在\"face_ort.png\"中。这幅图片和刚刚得到的\"face_torch.png\"是一模一样的。这说明 ONNX Runtime 成功运行了 SRCNN 模型，模型部署完成了！以后有用户想实现超分辨率的操作，我们只需要提供一个 \"srcnn.onnx\" 文件，并帮助用户配置好 ONNX Runtime 的 Python 环境，用几行代码就可以运行模型了。或者还有更简便的方法，我们可以利用 ONNX Runtime 编译出一个可以直接执行模型的应用程序。我们只需要给用户提供 ONNX 模型文件，并让用户在应用程序选择要执行的 ONNX 模型文件名就可以运行模型了。\n",
        "\n",
        "# 总结\n",
        "在这篇教程里，我们利用成熟的模型部署工具，轻松部署了一个初始版本的超分辨率模型 SRCNN。但在实际应用场景中，随着模型结构的复杂度不断加深，碰到的困难的也会越来越多。在下一篇教程里，我们将“升级”一下这个超分辨率模型，让它支持动态的输入。\n",
        "\n",
        "看完这篇教程，是不是感觉知识太多一下消化不过来？没关系，模型部署本身有非常多的东西要学。为了举例的方便，这篇教程包含了许多未来才会讲到的知识点。事实上，读完这篇教程后，记下以下知识点就够了：\n",
        "\n",
        "*   模型部署，指把训练好的模型在特定环境中运行的过程。模型部署要解决模型框架兼容性差和模型运行速度慢这两大问题。\n",
        "*   模型部署的常见流水线是“深度学习框架-中间表示-推理引擎”。其中比较常用的一个中间表示是 ONNX。\n",
        "*   深度学习模型实际上就是一个计算图。模型部署时通常把模型转换成静态的计算图，即没有控制流（分支语句、循环语句）的计算图。\n",
        "*   PyTorch 框架自带对 ONNX 的支持，只需要构造一组随机的输入，并对模型调用 **torch.onnx.export** 即可完成 PyTorch 到 ONNX 的转换。\n",
        "*   推理引擎 ONNX Runtime 对 ONNX 模型有原生的支持。给定一个 .onnx 文件，只需要简单使用 ONNX Runtime 的 Python API 就可以完成模型推理。\n",
        "\n",
        "为了实现深度学习算法的落地，充满挑战的模型部署是一个逃不开的步骤。为此，我们开发的开源库 MMDeploy 实现了 OpenMMLab 中目标检测、图像分割、超分辨率等多个视觉任务模型的部署，支持 ONNX Runtime，TensorRT，ncnn ，openppl，OpenVINO 等多个推理引擎。在后续的模型部署教程中，我们将在介绍模型部署技术的同时，介绍这些技术是如何运用在 MMDeploy 中的。希望大家继续关注我们的后续教程，关注 MMDeploy，共同为深度学习算法落地贡献自己的一份力。"
      ]
    }
  ],
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    },
    "kernelspec": {
      "display_name": "Python 3",
      "name": "python3"
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    "language_info": {
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